from __future__ import (absolute_import, division, print_function, unicode_literals)

import math
import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])
import pandas as pd
# from WindPy import w
import backtrader as bt
from matplotlib.cbook import todate
from lxml.html import FieldsDict
from math import nan
import time

# Create a Stratey
class TestStrategy(bt.Strategy):

    def log(self, txt, dt = None):
        ''''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close
        # To keep track of pending orders
        self.order = None
        # previous day's close
        self.previousClose = None

        # Add a MovingAverageSimple indicator
        self.sma = bt.indicators.MovingAverageSimple(self.datas[0], period=5)
    #         bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
    #         bt.indicators.WeightedMovingAverage(self.datas[0], period=25).subplot = True
    #         bt.indicators.MACDHisto(self.datas[0])
    #         rsi = bt.indicators.RSI(self.datas[0])
    #         bt.indicators.SmoothedMovingAverage(rsi, period=10)
    #         bt.indicators.ATR(self.datas[0]).plot = False
    #
    #         rsi = bt.indicators.RSI(self.datas[0])
    #         self.sma = bt.indicators.SmoothedMovingAverage(rsi, period=20)

    def start(self):
        print("hello world!")

    def notify(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enougth cash
        if order.status in [order.Completed, order.Canceled, order.Margin]:
            if order.isbuy():
                self.log('BUY EXECUTED, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        # Write down: no pending order
        self.order = None

    def next(self):
        if self.previousClose == None :
            self.previousClose = self.dataclose[0];
            return

        self.log('Close, %.2f' % self.dataclose[0])
        self.log('Previous close %.2f' % self.previousClose)
        self.log('MA %.2f' % self.sma[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return

        # Check if we are in the market
        if not self.position:

            # Not yet ... we MIGHT BUY if ...
            if self.previousClose > self.sma[0]:
                # BUY, BUY, BUY!!! (with default parameters)
                self.log('BUY CREATE %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:

            # Already in the market ... we might sell
            if self.previousClose < self.sma[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()

        self.previousClose = self.dataclose[0];

if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # Create a Data Feed
    # 数据必须包含open，close，high，low，volume，openinterest，日期是index
    # parse_dates=Ture 自动把数据中的符合日期的格式变成datetime类型
    dataframe = pd.read_csv("../analysis/000921.csv", index_col = 'trade_date', parse_dates = True)
    dataframe.rename(columns={'vol':'volume'}, inplace = True)
    dataframe.head(5)
    dataframe = dataframe.sort_index(ascending = True)
    #     dataframe = dataframe.head(5)
    dataframe['openinterest'] = 0
    data = bt.feeds.PandasData(dataname = dataframe)
    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # 设置每笔交易交易的股票数量  
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)
    # Set the commission  
    cerebro.broker.setcommission(commission=0.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    # Plot the result
    cerebro.plot()
